Monitoring machinery health and alerting operators to anomalous machinery conditions is an important part of operating one or a fleet of machines. Specifically, monitoring selected auxiliary system process parameters is important to health monitoring of gas turbine auxiliary systems. There is currently no known monitoring system for online estimation of most auxiliary system process parameters, and only the measured parameter is monitored. By not comparing the measured value to an expected value, the dynamic baseline and physical insight to define alarm thresholds are unknown. Without this calculation, only static thresholds based on constant deviation from preset values is available. Further, troubleshooting is hindered without an estimation of the auxiliary system process parameters. For example, a determination can be made as to the source of a deviation between the expected value and the measured value. Moreover, rapidly changing operational conditions or very slowly changing operational conditions may make it difficult for an operator to recognize anomalous conditions or what operational changes can be made to mitigate the anomalous conditions.
At least some known auxiliary system monitoring systems monitor the measured values only and using historical data for the same type of machine static thresholds are predefined, so that if the measured value exceeds the predefined threshold, an alarm is raised. Many attempts are needed to define and refine these thresholds, which do not take into account the machine running or load conditions. Such systems are prone to too many false alarms, and actual faults are generally detected too late. Moreover, only limited or no troubleshooting information is provided in such systems.